docs: def _add_evidence(
              self,
              assoc_id,
              eco_id,
              p_value,
              percentage_change,
              effect_size,
              study_bnode
      ):
          """
          :param assoc_id: assoc curie used to reify a
          genotype to phenotype association, generated in _process_data()
          :param eco_id: eco_id as curie, hardcoded in _process_data()
          :param p_value: str, from self.files['all']
          :param percentage_change: str, from self.files['all']
          :param effect_size: str, from self.files['all']
          :param study_bnode: str, from self.files['all']
          :param phenotyping_center: str, from self.files['all']
          :return: str, evidence_line_bnode as curie
          """
  
          evidence_model = Evidence(self.graph, assoc_id)
          provenance_model = Provenance(self.graph)
          model = Model(self.graph)
  
          # Add line of evidence
          evidence_line_bnode = self.make_id(
              "{0}{1}".format(assoc_id, study_bnode), '_')
          evidence_model.add_supporting_evidence(evidence_line_bnode)
          model.addIndividualToGraph(evidence_line_bnode, None, eco_id)
  
          # Add supporting measurements to line of evidence
          measurements = {}
          if p_value is not None or p_value != "":
              p_value_bnode = self.make_id(
                  "{0}{1}{2}".format(evidence_line_bnode, 'p_value', p_value), '_')
              model.addIndividualToGraph(p_value_bnode, None, self.globaltt['p-value'])
              try:
                  measurements[p_value_bnode] = float(p_value)
              except ValueError:
                  measurements[p_value_bnode] = p_value
          if percentage_change is not None and percentage_change != '':
  
              fold_change_bnode = self.make_id(
                  "{0}{1}{2}".format(
                      evidence_line_bnode, 'percentage_change', percentage_change), '_')
              model.addIndividualToGraph(
                  fold_change_bnode, None, self.resolve('percentage_change'))
              measurements[fold_change_bnode] = percentage_change
          if effect_size is not None or effect_size != "":
              fold_change_bnode = self.make_id(
                  "{0}{1}{2}".format(
                      evidence_line_bnode, 'effect_size', effect_size), '_')
              model.addIndividualToGraph(
                  fold_change_bnode, None, self.globaltt['effect size estimate'])
              measurements[fold_change_bnode] = effect_size
  
          evidence_model.add_supporting_data(evidence_line_bnode, measurements)
  
          # Link evidence to provenance by connecting to study node
          provenance_model.add_study_to_measurements(study_bnode, measurements.keys())
          self.graph.addTriple(
              evidence_line_bnode, self.globaltt['has_evidence_item_output_from'], study_bnode)
  
          return evidence_line_bnode